Sales Concessions in the US Housing Market

This article examines the use of concessions in the US housing market, specifically payments for closing costs, home warranties, and structural repairs. This is the first study to examine the motivations and characteristics of homeowners that utilize concessions. It also examines the impact concessions have on transaction prices and marketing durations. While the literature has attempted to determine if concessions can reduce marketing durations or increase transaction prices, the evidence is tainted by endogeneity and sample issues. Additionally, we find that relative bargaining power between buyers and sellers has a fundamental effect on how concessions alter prices and marketing durations. This aspect has been considered only narrowly in the extant literature. Our results demonstrate that when sellers have bargaining power, transactions including concessions exhibit higher prices and shorter marketing durations. Conversely, when buyers have greater negotiation leverage, transactions including concessions experience lower prices and longer marketing periods.     

The Impact of TOM on Prices in the US Housing Market

The Journal of Real Estate Finance and Economics - Search theory shows that real property prices and marketing durations are simultaneously determined and positively related. Yet, empirical studies...     

The US Housing Market: Asset Pricing Forecasts Using Time Varying Coefficients

The US housing market has experienced significant cyclical volatility over the last twenty-five years due to major structural changes and economic fluctuations. In addition, the housing market is generally considered to be weak form inefficient. Houses are relatively illiquid, exceptionally heterogeneous, and are associated with large transactions costs. As such, past research has shown that it is possible to predict, at least partially, the time path of housing prices. The ability to predict housing prices is important such that investors can make better asset allocation decisions, including the pricing and underwriting of mortgages. Most of the prior studies examining the US housing market have employed constant coefficient approaches to forecast house price movements. However, this approach is not optimal as an examination of data reveals substantial sub-sample parameter instability. To account for the parameter instability, we employ alternative estimation methodologies where the estimated parameters are allowed to vary over time. The results provide strong empirical evidence in favor of utilizing the rolling Generalized Autoregressive Conditional Heteroskedastic (GARCH) Model and the Kalman Filter with an Autoregressive Presentation (KAR) for the parameters time variation. Lastly, we provide out-of-sample forecasts and demonstrate the precision of our approach.     

Money: A Market Microstructure Approach

The new monetary economics predicts that deregulation and financial innovation will lead to a moneyless world. This paper uses a market microstructure approach to show that a common medium of exchange that serves as unit of account will remain a necessary instrument to reduce transaction costs. This finding is supported by empirical evidence from foreign exchange markets.     

Machine Learning Predictions of Housing Market Synchronization across US States: The Role of Uncertainty

The Journal of Real Estate Finance and Economics - We analyze the role of macroeconomic uncertainty in predicting synchronization in housing price movements across all the United States (US) states...     

Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach

Scaling techniques are proposed as a tool for the analysis and prediction of corporate failure. This approach, while keeping a strong theoretical basis, has the advantage of visualising the main features of the data in the form of statistical maps that lend themselves to intuitive interpretation. The maps contain directional statistics to help with interpretation. The methodology is demonstrated using a sample of UK industrial companies. A future‐dated holdout sample is also employed to illustrate how the Multidimensional Scaling technique can aid practitioners when assessing the financial health of a company.     

租金回报、债务偿付与均衡杠杆率——基于美国房产市场的实证研究

透过本轮由美国次级债市场引发的全球性金融危机,反映出由于信用扩张、资产价格与投资泡沫而产生的金融危机现象日益凸显.本文从均衡杠杆率的角度对此作出解释,实证研究结论表明美国家庭债务偿付率与房产租金回报率之间存在长期协整关系,债务偿付率(实际杠杆率)偏离租金回报率(均衡杠杆率)而产生的超额杠杆是本轮美国次贷危机爆发的主要原因,此外,房价预期偏差及低名义利率政策也是诱发美国房产市场泡沫及家庭过度杠杆的重要原因.本文最终结论:超额杠杆率作为危机的一个预警指标,远较金融系统的压力测试更具实际意义.     

Testing for Bubbles in Housing Markets: A Panel Data Approach

We employ recently developed cross-sectionally robust panel data tests for unit roots and cointegration to find whether house prices reflect house related earnings. We use U.S. data for Metropolitan Statistical Areas, with house price measured by the weighted-repeated-sales index and cash-flows by market tenants’ rents. In our full sample period, an error-correction model is not appropriate, i.e. there is a bubble. We then combine overlapping 10-year periods, price–rent ratios, and the panel data tests to construct a bubble indicator. The indicator is high for the late 1980s, early 1990s and since the late 1990s. Finally, evidence based on panel data Granger causality tests suggests that house price changes are helpful in predicting changes in rents and vice versa. CERGE-EI is a joint workplace of the Center for Economic Research and Graduate Education, Charles University, and the Economics Institute of the Academy of Sciences of the Czech Republic.     

A Tale of Two Countries: Comparing the US and Chinese Housing Markets

The Journal of Real Estate Finance and Economics - The recent surge in property values in China has been similar to the surge in the U.S before the crash in 2007. This raises concerns about whether...     

A Dynamic Model of the Housing Market: The Role of Vacancies

While the hedonic property value model and recently developed computable general equilibrium urban models assume the housing market is in equilibrium, recent years have witnessed extreme circumstances such as large changes in housing prices, high levels of mortgage default, and high levels of foreclosure that bring into question this assumption. This highlights the need for a better understanding of the dynamics of the housing market and the mechanisms that drive and sustain periods of disequilibrium. In this analysis, I develop a dynamic model of the housing market where vacancies naturally arise as the error correction mechanism. I estimate this model using annual U.S. panel data at the MSA level for 1990–2011. The results show that when there is excess demand, prices rise when vacancies fall but prices do not fall when there is excess supply and vacancies rise. This is consistent with the belief that prices are sticky downwards and hence prolong housing downturns. On the other hand, when there is excess supply, there is a relatively stronger decline in new housing in response to a rise in vacancies and much less of a new housing reaction when there is excess demand and vacancies fall. Furthermore, when I allow for a structural shift in the housing market brought on by the Great Recession (2006–2011), I find that the housing market became more responsive on both sides – excess supply and demand – during this period.     

Portfolio Capital Flows in Thailand: A Bayesian Model Averaging Approach

We study the gross and net terms of portfolio capital flows by examining their determinants. Through the application of the Bayesian model averaging method, the determinants are evaluated by a set of models instead of a single specification. Our findings show that the magnitude of both gross equity and gross debt flows are large, relative to their net terms. Equity inflows and outflows are quite symmetric with similar determinants; debt inflows and outflows are less symmetric. The paper provides partial evidence to support the importance of both internal and external factors as determinants of capital flows.     

Price-volume Correlation in the Housing Market: Causality and Co-movements

Housing market cycles are featured by a positive correlation of prices and trading volume, which is conventionally attributed to a causal relationship between prices and volume. This paper analyzes the housing markets in 114 metropolitan statistical areas in the United States from 1990 to 2002, treats both prices and volume as endogenous variables, and studies whether and how exogenous shocks cause co-movements of prices and volume. At quarterly frequency, we find that, first, both home prices and trading volume are affected by conditions in labor markets, the mortgage market, and the stock market, and the effects differ between markets with low and high supply elasticity. Second, home prices Granger cause trading volume, but the effects are asymmetric—decreases in prices reduce trading volume, and increases in prices have no effect. Third, trading volume also Granger causes home prices, but only in markets with inelastic supply. Finally, we find a statistically significant positive price–volume correlation; which, however, is mainly explained by co-movements of prices and volume caused by exogenous shocks, instead of the Granger causality between prices and volume.     

Housing Quality in the Forward Contracts Market

Developers often conduct forward sales (or presales) before building completion to relieve financial risk and burden. However, there are worries that housing units sold in this way will turn out to be substandard because developers, who have been paid for the unfinished units, may have incentives to cut costs by lowering the quality. This is a typical moral hazard problem. Nonetheless, forward sales have been very popular in some Asian cities such as Hong Kong, Singapore, and Taiwan. A plausible explanation is that the market has efficiently adjusted the forward price for this potential quality problem according to developers’ reputations. This paper aims to theoretically explain and empirically test (1) whether reputation is reflected in forward prices and (2) whether the expected quality level matches with the actual quality level. Using the forward and spot sales data of the Hong Kong real estate market, we found that even though housing quality was not observable during presales, the market was able to capitalize developers’ reputations into forward prices accurately. This suggests that the optimal strategy for developers is to stick to the quality level implied by their reputations. A paper submitted to Journal of Real Estate Finance and Economics. A Special Issue for the 2005 NUS-HKU Symposium on Real Estate Research.     

Housing Supply: The Other Half of the Market A Note from the Editor

The Journal of Real Estate Finance and Economics -     

Predicting Volatility in the Foreign Exchange Market

Measures of volatility implied in option prices are widely believed to be the best available volatility forecasts. In this article, we examine the information content and predictive power of implied standard deviations (ISDs) derived from Chicago Mercantile Exchange options on foreign currency futures. The article finds that statistical time-series models, even when given the advantage of “ex post” parameter estimates, are outperformed by ISDs. ISDs, however, also appear to be biased volatility forecasts. Using simulations to investigate the robustness of these results, the article finds that measurement errors and statistical problems can substantially distort inferences. Even accounting for these, however, ISDs appear to be too variable relative to future volatility.     

Spatial Dependence in the Residential Canadian Housing Market

The Journal of Real Estate Finance and Economics - This paper studies the spatial dependence of residential resale housing returns in ten major Canadian Census Metropolitan areas (or CMAs) from...     

Duration of Residence in the Rental Housing Market

This paper estimates a proportional hazard model of duration of residence in rental housing over 1987–1998 based on a unique dataset from the BLS-CPI housing sample together with American Housing Survey and other metropolitan economic data. The paper employs an innovative semi-parametric estimation approach for group duration analysis of the proportional hazard model. Results of the analysis indicate that the duration of residence in rental housing varies significantly across individual units and market segments, and is effected by tenant, dwelling, and market characteristics. An improved understanding of duration of residence offers new insights as regards fluctuations in tenant turnover, building occupancy, and rent flows, as well as new confidence in pro forma assumptions critical to rental housing development.